Identification, Elucidation and Deployment of a Cytoplasmic Male Sterility System for Hybrid Potato.

Recent advances in diploid F1 hybrid potato breeding rely on the production of inbred lines using the S-locus inhibitor (Sli) gene. As a result of this method, female parent lines are self-fertile and require emasculation before hybrid seed production. The resulting F1 hybrids are self-fertile as well and produce many undesirable berries in the field. Utilization of cytoplasmic male sterility would eliminate the need for emasculation, resulting in more efficient hybrid seed production and male sterile F1 hybrids. We observed plants that completely lacked anthers in an F2 population derived from an interspecific cross between diploid S. tuberosum and S. microdontum. We studied the antherless trait to determine its suitability for use in hybrid potato breeding. We mapped the causal locus to the short arm of Chromosome 6, developed KASP markers for the antherless (al) locus and introduced it into lines with T and A cytoplasm. We found that antherless type male sterility is not expressed in T and A cytoplasm, proving that it is a form of CMS. We hybridized male sterile al/al plants with P cytoplasm with pollen from al/al plants with T and A cytoplasm and we show that the resulting hybrids set significantly fewer berries in the field. Here, we show that the antherless CMS system can be readily deployed in diploid F1 hybrid potato breeding to improve hybridization efficiency and reduce berry set in the field.

A survey of the Sli gene in wild and cultivated potato.

Inbred-hybrid breeding of diploid potatoes necessitates breeding lines that are self-compatible. One way of incorporating self-compatibility into incompatible cultivated potato (Solanum tuberosum) germplasm is to introduce the S-locus inhibitor gene (Sli), which functions as a dominant inhibitor of gametophytic self-incompatibility. To learn more about Sli diversity and function in wild species relatives of cultivated potato, we obtained Sli gene sequences that extended from the 5'UTR to the 3'UTR from 133 individuals from 22 wild species relatives of potato and eight diverse cultivated potato clones. DNA sequence alignment and phylogenetic trees based on genomic and protein sequences show that there are two highly conserved groups of Sli sequences. DNA sequences in one group contain the 533 bp insertion upstream of the start codon identified previously in self-compatible potato. The second group lacks the insertion. Three diploid and four polyploid individuals of wild species collected from geographically disjointed localities contained Sli with the 533 bp insertion. For most of the wild species clones examined, however, Sli did not have the insertion. Phylogenetic analysis indicated that Sli sequences with the insertion, in wild species and in cultivated clones, trace back to a single origin. Some diploid wild potatoes that have Sli with the insertion were self-incompatible and some wild potatoes that lack the insertion were self-compatible. Although there is evidence of positive selection for some codon positions in Sli, there is no evidence of diversifying selection at the gene level. In silico analysis of Sli protein structure did not support the hypothesis that amino acid changes from wild-type (no insertion) to insertion-type account for changes in protein function. Our study demonstrated that genetic factors besides the Sli gene must be important for conditioning a switch in the mating system from self-incompatible to self-compatible in wild potatoes.

The effect of marker types and density on genomic prediction and GWAS of key performance traits in tetraploid potato.

Genomic prediction and genome-wide association studies are becoming widely employed in potato key performance trait QTL identifications and to support potato breeding using genomic selection. Elite cultivars are tetraploid and highly heterozygous but also share many common ancestors and generation-spanning inbreeding events, resulting from the clonal propagation of potatoes through seed potatoes. Consequentially, many SNP markers are not in a 1:1 relationship with a single allele variant but shared over several alleles that might exert varying effects on a given trait. The impact of such redundant "diluted" predictors on the statistical models underpinning genome-wide association studies (GWAS) and genomic prediction has scarcely been evaluated despite the potential impact on model accuracy and performance. We evaluated the impact of marker location, marker type, and marker density on the genomic prediction and GWAS of five key performance traits in tetraploid potato (chipping quality, dry matter content, length/width ratio, senescence, and yield). A 762-offspring panel of a diallel cross of 18 elite cultivars was genotyped by sequencing, and markers were annotated according to a reference genome. Genomic prediction models (GBLUP) were trained on four marker subsets [non-synonymous (29,553 SNPs), synonymous (31,229), non-coding (32,388), and a combination], and robustness to marker reduction was investigated. Single-marker regression GWAS was performed for each trait and marker subset. The best cross-validated prediction correlation coefficients of 0.54, 0.75, 0.49, 0.35, and 0.28 were obtained for chipping quality, dry matter content, length/width ratio, senescence, and yield, respectively. The trait prediction abilities were similar across all marker types, with only non-synonymous variants improving yield predictive ability by 16%. Marker reduction response did not depend on marker type but rather on trait. Traits with high predictive abilities, e.g., dry matter content, reached a plateau using fewer markers than traits with intermediate-low correlations, such as yield. The predictions were unbiased across all traits, marker types, and all marker densities >100 SNPs. Our results suggest that using non-synonymous variants does not enhance the performance of genomic prediction of most traits. The major known QTLs were identified by GWAS and were reproducible across exonic and whole-genome variant sets for dry matter content, length/width ratio, and senescence. In contrast, minor QTL detection was marker type dependent.

Exploring the Impact of Coconut Peat and Vermiculite on the Rhizosphere Microbiome of Pre-Basic Seed Potatoes under Soilless Cultivation Conditions.

Soilless cultivation of potatoes often utilizes organic coconut peat and inorganic vermiculite as growing substrates. The unique microbial communities and physicochemical characteristics inherent to each substrate significantly influence the microecological environment crucial for potato growth and breeding. This study analyzed environmental factors within each substrate and employed Illumina sequencing alongside bioinformatics tools to examine microbial community structures, their correlation with environmental factors, core microbial functions, and the dynamics of microbial networks across various samples. These included pure coconut peat (CP1) and pure vermiculite (V1), substrates mixed with organic fertilizer for three days (CP2 and V2), and three combinations cultivated with potatoes for 50 days (CP3, V3, and CV3-a 1:1 mix of coconut peat and vermiculite with organic fertilizer). Vermiculite naturally hosts a more diverse microbial community. After mixing with fertilizer and composting for 3 days, and 50 days of potato cultivation, fungal diversity decreased in both substrates. Coconut peat maintains higher bacterial diversity and richness compared to vermiculite, harboring more beneficial bacteria and fungi, resulting in a more complex microbial network. However, vermiculite shows lower bacterial diversity and richness, with an accumulation of pathogenic microorganisms. Among the 11 environmental factors tested, water-soluble nitrogen (WSN), total nitrogen (TN), available potassium (AK), total organic carbon (TOC) and air-filled porosity (AFP) were significantly associated with microbial succession in the substrate.The nutritional type composition and interaction patterns of indigenous microorganisms differ between vermiculite and coconut peat. Adding abundant nutrients significantly affects the stability and interaction of the entire microbial community, even post-potato cultivation. When using vermiculite for soilless cultivation, precise control and adjustment of nutrient addition quantity and frequency are essential.

A k-mer-based bulked segregant analysis approach to map seed traits in unphased heterozygous potato genomes.

High-throughput sequencing-based methods for bulked segregant analysis (BSA) allow for the rapid identification of genetic markers associated with traits of interest. BSA studies have successfully identified qualitative (binary) and quantitative trait loci (QTLs) using QTL mapping. However, most require population structures that fit the models available and a reference genome. Instead, high-throughput short-read sequencing can be combined with BSA of k-mers (BSA-k-mer) to map traits that appear refractory to standard approaches. This method can be applied to any organism and is particularly useful for species with genomes diverged from the closest sequenced genome. It is also instrumental when dealing with highly heterozygous and potentially polyploid genomes without phased haplotype assemblies and for which a single haplotype can control a trait. Finally, it is flexible in terms of population structure. Here, we apply the BSA-k-mer method for the rapid identification of candidate regions related to seed spot and seed size in diploid potato. Using a mixture of F1 and F2 individuals from a cross between 2 highly heterozygous parents, candidate sequences were identified for each trait using the BSA-k-mer approach. Using parental reads, we were able to determine the parental origin of the loci. Finally, we mapped the identified k-mers to a closely related potato genome to validate the method and determine the genomic loci underlying these sequences. The location identified for the seed spot matches with previously identified loci associated with pigmentation in potato. The loci associated with seed size are novel. Both loci are relevant in future breeding toward true seeds in potato.

Crossover shortage in potato is caused by StMSH4 mutant alleles and leads to either highly uniform unreduced pollen or sterility.

The balanced segregation of homologous chromosomes during meiosis is essential for fertility and is mediated by crossovers (COs). A strong reduction of CO number leads to the unpairing of homologous chromosomes after the withdrawal of the synaptonemal complex. This results in the random segregation of univalents during meiosis I and ultimately to the production of unbalanced and sterile gametes. However, if CO shortage is combined with another meiotic alteration that restitutes the first meiotic division, then uniform and balanced unreduced male gametes, essentially composed of nonrecombinant homologs, are produced. This mitosis-like division is of interest to breeders because it transmits most of the parental heterozygosity to the gametes. In potato, CO shortage, a recessive trait previously referred to as desynapsis, was tentatively mapped to chromosome 8. In this article, we have fine-mapped the position of the CO shortage locus and identified StMSH4, an essential component of the class I CO pathway, as the most likely candidate gene. A 7 base-pair insertion in the second exon of StMSH4 was found to be associated with CO shortage in our mapping population. We also identified a second allele with a 3,820 base-pair insertion and confirmed that both alleles cannot complement each other. Such nonfunctional alleles appear to be common in potato cultivars. More than half of the varieties we tested are carriers of mutational load at the StMSH4 locus. With this new information, breeders can choose to remove alleles associated with CO shortage from their germplasm to improve fertility or to use them to produce highly uniform unreduced male gametes in alternative breeding schemes.

Challenges for crop improvement.

The genetic improvement of crops faces the significant challenge of feeding an ever-increasing population amidst a changing climate, and when governments are adopting a 'more with less' approach to reduce input use. Plant breeding has the potential to contribute to the United Nations Agenda 2030 by addressing various sustainable development goals (SDGs), with its most profound impact expected on SDG2 Zero Hunger. To expedite the time-consuming crossbreeding process, a genomic-led approach for predicting breeding values, targeted mutagenesis through gene editing, high-throughput phenomics for trait evaluation, enviromics for including characterization of the testing environments, machine learning for effective management of large datasets, and speed breeding techniques promoting early flowering and seed production are being incorporated into the plant breeding toolbox. These advancements are poised to enhance genetic gains through selection in the cultigen pools of various crops. Consequently, these knowledge-based breeding methods are pursued for trait introgression, population improvement, and cultivar development. This article uses the potato crop as an example to showcase the progress being made in both genomic-led approaches and gene editing for accelerating the delivery of genetic gains through the utilization of genetically enhanced elite germplasm. It also further underscores that access to technological advances in plant breeding may be influenced by regulations and intellectual property rights.

HT-B and S-RNase CRISPR-Cas9 double knockouts show enhanced self-fertility in diploid Solanum tuberosum.

The Gametophytic Self-Incompatibility (GSI) system in diploid potato (Solanum tuberosum L.) poses a substantial barrier in diploid potato breeding by hindering the generation of inbred lines. One solution is gene editing to generate self-compatible diploid potatoes which will allow for the generation of elite inbred lines with fixed favorable alleles and heterotic potential. The S-RNase and HT genes have been shown previously to contribute to GSI in the Solanaceae family and self-compatible S. tuberosum lines have been generated by knocking out S-RNase gene with CRISPR-Cas9 gene editing. This study employed CRISPR-Cas9 to knockout HT-B either individually or in concert with S-RNase in the diploid self-incompatible S. tuberosum clone DRH-195. Using mature seed formation from self-pollinated fruit as the defining characteristic of self-compatibility, HT-B-only knockouts produced little or no seed. In contrast, double knockout lines of HT-B and S-RNase displayed levels of seed production that were up to three times higher than observed in the S-RNase-only knockout, indicating a synergistic effect between HT-B and S-RNase in self-compatibility in diploid potato. This contrasts with compatible cross-pollinations, where S-RNase and HT-B did not have a significant effect on seed set. Contradictory to the traditional GSI model, self-incompatible lines displayed pollen tube growth reaching the ovary, yet ovules failed to develop into seeds indicating a potential late-acting self-incompatibility in DRH-195. Germplasm generated from this study will serve as a valuable resource for diploid potato breeding.

Converting Hybrid Potato Breeding Science into Practice.

Research on diploid hybrid potato has made fast advances in recent years. In this review we give an overview of the most recent and relevant research outcomes. We define different components needed for a complete hybrid program: inbred line development, hybrid evaluation, cropping systems and variety registration. For each of these components the important research results are discussed and the outcomes and issues that merit further study are identified. We connect fundamental and applied research to application in a breeding program, based on the experiences at the breeding company Solynta. In the concluding remarks, we set hybrid breeding in a societal perspective, and we identify bottlenecks that need to be overcome to allow successful adoption of hybrid potato.

Diversity and population structure of Nordic potato cultivars and breeding clones.

BACKGROUND: The genetic diversity and population structure of breeding germplasm is central knowledge for crop improvement. To gain insight into the genetic potential of the germplasm used for potato breeding in a Nordic breeding program as well as all available accessions from the Nordic genebank (NordGen), 133 potato genotypes were genotyped using the Infinium Illumina 20 K SNP array. After SNP filtering, 11 610 polymorphic SNPs were included in the analysis. In addition, data from three important breeding traits - percent dry matter and uniformity of tuber shape and eye - were scored to measure the variation potato cultivars and breeding clones. RESULTS: The genetic diversity among the genotypes was estimated using principal coordinate analysis based on the genetic distance between individuals, as well as by using the software STRUCTURE. Both methods suggest that the collected breeding material and the germplasm from the gene-bank are closely related, with a low degree of population structure between the groups. The phenotypic distribution among the genotypes revealed significant differences, especially between farmer's cultivars and released cultivars and breeding clones. The percent heterozygosity was similar between the groups, with a mean average of 58-60%. Overall, the breeding germplasm and the accessions from the Nordic genebank seems to be closely related with similar genetic background. CONCLUSION: The genetic potential of available Nordic potato breeding germplasm is low, and for genetic hybridization purposes, genotypes from outside the Nordic region should be employed.

Genetic Diversity Trends in the Cultivated Potato: A Spatiotemporal Overview.

We investigated the changes in genetic diversity over time and space of the cultivated potato (Solanum tuberosum L.) for the period pre-1800 to 2021. A substantial panel of 1219 potato varieties, belonging to different spatiotemporal groups, was examined using a set of 35 microsatellite markers (SSR). Genotypic data covering a total of 407 alleles was analyzed using both self-organizing map (SOM) and discriminant analysis of principal components (DAPC) de novo and a priori clustering methods, respectively. Data analysis based on different models of genetic structuring provided evidence of (1) at least two early lineages that have been maintained since their initial introduction from the Andes into Europe in the 16th century, followed by later ones coming from reintroduction events from the US in the mid-1800s; (2) a level of diversity that has gradually evolved throughout the studied time periods and areas, with the most modern variety groups encompassing most of the diversity found in earlier decades; (3) the emergence of new genetic groups within the current population due to increases in the use of germplasm enhancement practices using exotic germplasms. In addition, analysis revealed significant genetic differentiation both among and within the spatiotemporal groups of germplasm studied. Our results therefore highlight that no major genetic narrowing events have occurred within the cultivated potato over the past three centuries. On the contrary, the genetic base shows promising signs of improvement, thanks to extensive breeding work that is gaining momentum. This overview could be drawn on not only to understand better how past decisions have impacted the current genetic cultivated potato resources, but also to develop appropriate new strategies for breeding programs consistent with the socio-economic and sustainability challenges faced by agrifood systems.

Genome-Based Genotype × Environment Prediction Enhances Potato (Solanum tuberosum L.) Improvement Using Pseudo-Diploid and Polysomic Tetraploid Modeling.

Potato breeding must improve its efficiency by increasing the reliability of selection as well as identifying a promising germplasm for crossing. This study shows the prediction accuracy of genomic-estimated breeding values for several potato (Solanum tuberosum L.) breeding clones and the released cultivars that were evaluated at three locations in northern and southern Sweden for various traits. Three dosages of marker alleles [pseudo-diploid (A), additive tetrasomic polyploidy (B), and additive-non-additive tetrasomic polyploidy (C)] were considered in the genome-based prediction models, for single environments and multiple environments (accounting for the genotype-by-environment interaction or G × E), and for comparing two kernels, the conventional linear, Genomic Best Linear Unbiased Prediction (GBLUP) (GB), and the non-linear Gaussian kernel (GK), when used with the single-kernel genetic matrices of A, B, C, or when employing two-kernel genetic matrices in the model using the kernels from B and C for a single environment (models 1 and 2, respectively), and for multi-environments (models 3 and 4, respectively). Concerning the single site analyses, the trait with the highest prediction accuracy for all sites under A, B, C for model 1, model 2, and for GB and GK methods was tuber starch percentage. Another trait with relatively high prediction accuracy was the total tuber weight. Results show an increase in prediction accuracy of model 2 over model 1. Non-linear Gaussian kernel (GK) did not show any clear advantage over the linear kernel GBLUP (GB). Results from the multi-environments had prediction accuracy estimates (models 3 and 4) higher than those obtained from the single-environment analyses. Model 4 with GB was the best method in combination with the marker structure B for predicting most of the tuber traits. Most of the traits gave relatively high prediction accuracy under this combination of marker structure (A, B, C, and B-C), and methods GB and GK combined with the multi-environment with G × E model.

The power of genomic estimated breeding values for selection when using a finite population size in genetic improvement of tetraploid potato.

Potato breeding relies heavily on visual phenotypic scoring for clonal selection. Obtaining robust phenotypic data can be labor intensive and expensive, especially in the early cycles of a potato breeding program where the number of genotypes is very large. We have investigated the power of genomic estimated breeding values (GEBVs) for selection from a limited population size in potato breeding. We collected genotypic data from 669 tetraploid potato clones from all cycles of a potato breeding program, as well as phenotypic data for eight important breeding traits. The genotypes were partitioned into a training and a test population distinguished by cycle of selection in the breeding program. GEBVs for seven traits were predicted for individuals from the first stage of the breeding program (T1) which had not undergone any selection, or individuals selected at least once in the field (T2). An additional approach in which GEBVs were predicted within and across full-sib families from unselected material (T1) was tested for four breeding traits. GEBVs were obtained by using a Bayesian Ridge Regression model estimating single marker effects and phenotypic data from individuals at later stages of selection of the breeding program. Our results suggest that, for most traits included in this study, information from individuals from later stages of selection cannot be utilized to make selections based on GEBVs in earlier clonal generations. Predictions of GEBVs across full-sib families yielded similarly low prediction accuracies as across generations. The most promising approach for selection using GEBVs was found to be making predictions within full-sib families.

Resisting Potato Cyst Nematodes With Resistance.

Potato cyst nematodes (PCN) are economically important pests with a worldwide distribution in all temperate regions where potatoes are grown. Because above ground symptoms are non-specific, and detection of cysts in the soil is determined by the intensity of sampling, infestations are frequently spread before they are recognised. PCN cysts are resilient and persistent; their cargo of eggs can remain viable for over two decades, and thus once introduced PCN are very difficult to eradicate. Various control methods have been proposed, with resistant varieties being a key environmentally friendly and effective component of an integrated management programme. Wild and landrace relatives of cultivated potato have provided a source of PCN resistance genes that have been used in breeding programmes with varying levels of success. Producing a PCN resistant variety requires concerted effort over many years before it reaches what can be the biggest hurdle-commercial acceptance. Recent advances in potato genomics have provided tools to rapidly map resistance genes and to develop molecular markers to aid selection during breeding. This review will focus on the translation of these opportunities into durably PCN resistant varieties.

A Bioinformatics Pipeline to Identify a Subset of SNPs for Genomics-Assisted Potato Breeding.

Modern potato breeding methods following a genomic-led approach provide means for shortening breeding cycles and increasing breeding efficiency across selection cycles. Acquiring genetic data for large breeding populations remains expensive. We present a pipeline to reduce the number of single nucleotide polymorphisms (SNPs) to lower the cost of genotyping. First, we reduced the number of individuals to be genotyped with a high-throughput method according to the multi-trait variation as defined by principal component analysis of phenotypic characteristics. Next, we reduced the number of SNPs by pruning for linkage disequilibrium. By adjusting the square of the correlation coefficient between two adjacent loci, we obtained reduced subsets of SNPs. We subsequently tested these SNP subsets by two methods; (1) a genome-wide association study (GWAS) for marker identification, and (2) genomic selection (GS) to predict genomic estimated breeding values. The results indicate that both GWAS and GS can be done without loss of information after SNP reduction. The pipeline allows for creating custom SNP subsets to cover all variation found in any particular breeding population. Low-throughput genotyping will reduce the genotyping cost associated with large populations, thereby making genomic breeding methods applicable to large potato breeding populations by reducing genotyping costs.

Screening for Resistance to PVY in Australian Potato Germplasm.

Potatoes are an important human food crop, but have a number of yield limiting factors, including disease susceptibility. Potato virus Y (PVY) is found worldwide, and is one of the main virus problems for potato growers. PVY is transmitted by aphids and mechanically by machinery, tools and people, and symptoms are variable across cultivars and strains, including being symptomless in some cultivars. Therefore, breeding resistant cultivars is the best way to control this virus. This study phenotypically screened 74 of the main commercial cultivars and a few other select cultivars grown in Australia, in order to identify sources of resistance to PVY. The cultivars were screened against PVYO and PVYNTN, with 23 out of 71 resistant to PVYO and 13 out of 74 resistant to PVYNTN, and all these 13 were resistant to both strains. When the phenotypic screening was compared to the results listed on the European Cultivated Potato Database, the majority of results were found to be consistent. We then evaluated three molecular markers RYSC3, M45, and STM0003 for the extreme resistance genes Ryadg and Rysto, to validate the usefulness of the markers for marker-assisted selection (MAS) on Australian germplasm. The degree of correlation between the resistance phenotypes and the RYSC3, M45, and STM0003 markers for Ryadg and Rysto conferred PVY resistance was determined. Three cultivars amplified the RYSC3 marker, while the M45 marker amplified the same 3 and an additional 9. Of the 12 cultivars, 11 phenotyped as resistant, but 1 was susceptible. The STM0003 marker was amplified from only 2 cultivars that both had resistant phenotypes. The RYSC3, M45, and STM0003 markers were therefore able to identify all the 13 cultivars that were resistant to both strains of PVY. Therefore, these markers will enable the identification of genotypes with resistance to PVY, and enable PVY resistant parents to be used for the development of superior progeny; these genetic markers can be used for MAS in the Australian potato breeding program.

Transcriptome Profiling and Characterization of Drought-Tolerant Potato Plant (Solanum tuberosum L.).

Potato (Solanum tuberosum L.) is the third most important food crop, and breeding drought-tolerant varieties is vital research goal. However, detailed molecular mechanisms in response to drought stress in potatoes are not well known. In this study, we developed EMS-mutagenized potatoes that showed significant tolerance to drought stress compared to the wild-type (WT) 'Desiree' cultivar. In addition, changes to transcripts as a result of drought stress in WT and drought-tolerant (DR) plants were investigated by de novo assembly using the Illumina platform. One-week-old WT and DR plants were treated with -1.8 Mpa polyethylene glycol-8000, and total RNA was prepared from plants harvested at 0, 6, 12, 24, and 48 h for subsequent RNA sequencing. In total, 61,100 transcripts and 5,118 differentially expressed genes (DEGs) displaying up- or down-regulation were identified in pairwise comparisons of WT and DR plants following drought conditions. Transcriptome profiling showed the number of DEGs with up-regulation and down-regulation at 909, 977, 1181, 1225 and 826 between WT and DR plants at 0, 6, 12, 24, and 48 h, respectively. Results of KEGG enrichment showed that the drought tolerance mechanism of the DR plant can mainly be explained by two aspects, the 'photosynthetic-antenna protein' and 'protein processing of the endoplasmic reticulum'. We also divided eight expression patterns in four pairwise comparisons of DR plants (DR0 vs DR6, DR12, DR24, DR48) under PEG treatment. Our comprehensive transcriptome data will further enhance our understanding of the mechanisms regulating drought tolerance in tetraploid potato cultivars.

Association of Patatin-Based Proteomic Distances with Potato ( Solanum tuberosum L.) Quality Traits.

Patatin is the major tuber storage protein constituted by multiple isoforms highly variable across potato ( S. tuberosum) varieties. Here, we report a first association study of the variability of patatin isoforms between cultivars with their differences in tuber quality traits. Patatin-based proteomic distances were assessed between 15 table and/or processing potato cultivars from profiles of patatin obtained by two-dimensional electrophoresis. The content of ash, dry matter, reducing sugars, starch, total protein, and amino acid composition was also evaluated in tubers of each cultivar. Results showed that proteomic distances were significantly ( P < 0.05) associated with differences in the content of ash, dry matter, and essential amino acids. Proteomic distances were also able to identify outlier cultivars regarding the content of dry matter, content of protein, and protein quality. In conclusion, patatin-based proteomic distances can shorten the screening and selection processes of potato cultivars with advantageous characteristics in molecular breeding.

The Value of Expanding the Training Population to Improve Genomic Selection Models in Tetraploid Potato.

Genomic selection (GS) is becoming increasingly applicable to crops as the genotyping costs continue to decrease, which makes it an attractive alternative to traditional selective breeding based on observed phenotypes. With genome-wide molecular markers, selection based on predictions from genotypes can be made in the absence of direct phenotyping. The reliability of predictions depends strongly on the number of individuals used for training the predictive algorithms, particularly in a highly genetically diverse organism such as potatoes; however, the relationship between the individuals also has an enormous impact on prediction accuracy. Here we have studied genomic prediction in three different panels of potato cultivars, varying in size, design, and phenotypic profile. We have developed genomic prediction models for two important agronomic traits of potato, dry matter content and chipping quality. We used genotyping-by-sequencing to genotype 1,146 individuals and generated genomic prediction models from 167,637 markers to calculate genomic estimated breeding values with genomic best linear unbiased prediction. Cross-validated prediction correlations of 0.75-0.83 and 0.39-0.79 were obtained for dry matter content and chipping quality, respectively, when combining the three populations. These prediction accuracies were similar to those obtained when predicting performance within each panel. In contrast, but not unexpectedly, predictions across populations were generally lower, 0.37-0.71 and 0.28-0.48 for dry matter content and chipping quality, respectively. These predictions are not limited by the number of markers included, since similar prediction accuracies could be obtained when using merely 7,800 markers (<5%). Our results suggest that predictions across breeding populations in tetraploid potato are presently unreliable, but that individual prediction models within populations can be combined in an additive fashion to obtain high quality prediction models relevant for several breeding populations.

Use of easy measurable phenotypic traits as a complementary approach to evaluate the population structure and diversity in a high heterozygous panel of tetraploid clones and cultivars.

BACKGROUND: Diversity in crops is fundamental for plant breeding efforts. An accurate assessment of genetic diversity, using molecular markers, such as single nucleotide polymorphism (SNP), must be able to reveal the structure of the population under study. A characterization of population structure using easy measurable phenotypic traits could be a preliminary and low-cost approach to elucidate the genetic structure of a population. A potato population of 183 genotypes was evaluated using 4859 high-quality SNPs and 19 phenotypic traits commonly recorded in potato breeding programs. A Bayesian approach, Minimum Spanning Tree (MST) and diversity estimator, as well as multivariate analysis based on phenotypic traits, were adopted to assess the population structure. RESULTS: Analysis based on molecular markers showed groups linked to the phylogenetic relationship among the germplasm as well as the link with the breeding program that provided the material. Diversity estimators consistently structured the population according to a priori group estimation. The phenotypic traits only discriminated main groups with contrasting characteristics, as different subspecies, ploidy level or membership in a breeding program, but were not able to discriminate within groups. A joint molecular and phenotypic characterization analysis discriminated groups based on phenotypic classification, taxonomic category, provenance source of genotypes and genetic background. CONCLUSIONS: This paper shows the significant level of diversity existing in a parental population of potato as well as the putative phylogenetic relationships among the genotypes. The use of easily measurable phenotypic traits among highly contrasting genotypes could be a reasonable approach to estimate population structure in the initial phases of a potato breeding program.